Tag: Sequencing

BatchPrimer3 1.0 – High Throughput Web Application for PCR and Sequencing Primer Design

BatchPrimer3 1.0

:: DESCRIPTION

BatchPrimer3 is a comprehensive web primer design program using Primer3 core program as a major primer design engine to design different types of PCR primers and sequencing primers in a high-through manner. BatchPrimer3 allows users to design several types of primers including generic primers, hybridization oligos, SSR primers together with SSR detection, and SNP genotyping primers (including single-base extension primers, allele-specific primers, and tetra-primers for tetra-primer ARMS PCR), as well as DNA sequencing primers. A batch input of large number of sequences and a tab-delimited result output greatly facilitates rapid primer design and ordering process.

::DEVELOPER

Department of Plant Sciences, University of California

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Perl

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation

BatchPrimer3: a high throughput web application for PCR and sequencing primer design.
You FM, Huo N, Gu YQ, Luo MC, Ma Y, Hane D, Lazo GR, Dvorak J, Anderson OD.
BMC Bioinformatics. 2008 May 29;9:253.

SEECER 0.1.3 – SEquencing Error CorrEction for Rna reads

SEECER 0.1.3

:: DESCRIPTION

SEECER is an error correction method that removes errors that are introduced during sequencing. Mismatches, insertion or deletions are removed by creating multiple alignments of reads and building HMMs that are used to decide which reads are be corrected. In the provided reference it is shown that error correction with SEECER improves the downstream analysis, especially RNA de novo assembly.

::DEVELOPER

Hai-Son Le , Marcel Schulz , Ziv Bar-Joseph

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 SEECER

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 May 1;41(10):e109. doi: 10.1093/nar/gkt215
Probabilistic error correction for RNA sequencing.
Le HS, Schulz MH, McCauley BM, Hinman VF, Bar-Joseph Z.

PepNovo 20120423 – De novo Sequencing of low Precision MS/MS Data

PepNovo 20120423

:: DESCRIPTION

PepNovo is a de novo sequencing algorithm for MS/MS spectra. PepNovo accepts MS/MS spectra in the following formats: dta,mgf,mzxml. This version of PepNovo is optimized for ion-trap mass spectromtetry that uses CID fragmentation (charges 1-3, dominant b/y ladders).

::DEVELOPER

Ari Frank

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/windows

:: DOWNLOAD

 PepNovo

:: MORE INFORMATION

Citation:

Predicting Intensity Ranks of Peptide Fragment Ions
Frank, A.M.
J. Proteome Research, 8:2226-2240, 2009

RLM – Read level DNA methylation analysis of Bisulfite Converted Sequencing data

RLM

:: DESCRIPTION

RLM is a fast and scalable tool for the computation of frequently used Read-Level Methylation statistics.

::DEVELOPER

RLM Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R
:: DOWNLOAD

RLM

:: MORE INFORMATION

Citation

Hetzel S, Giesselmann P, Reinert K, Meissner A, Kretzmer H.
RLM: Fast and simplified extraction of Read-Level Methylation metrics from bisulfite sequencing data.
Bioinformatics. 2021 Oct 2:btab663. doi: 10.1093/bioinformatics/btab663. Epub ahead of print. PMID: 34601556.

Scirpy v0.10.1 – Scanpy Extension for analyzing Single-cell T-cell Receptor-sequencing data

Scirpy v0.10.1

:: DESCRIPTION

Scirpy is a scalable python-toolkit to analyse T cell receptor (TCR) or B cell receptor (BCR) repertoires from single-cell RNA sequencing (scRNA-seq) data. It seamlessly integrates with the popular scanpy library and provides various modules for data import, analysis and visualization.

::DEVELOPER

the Institute of Bioinformatics, Innsbruck Medical University

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

Scirpy

:: MORE INFORMATION

Citation

Sturm G, Szabo T, Fotakis G, Haider M, Rieder D, Trajanoski Z, Finotello F.
Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data.
Bioinformatics. 2020 Sep 15;36(18):4817-4818. doi: 10.1093/bioinformatics/btaa611. PMID: 32614448; PMCID: PMC7751015.

AscatNGS 4.4.1 – Somatic Copy Number analysis using WGS paired end wholegenome sequencing

AscatNGS 4.4.1

:: DESCRIPTION

AscatNGS contains the Cancer Genome Projects workflow implementation of the ASCAT copy number algorithm for paired end sequencing.

::DEVELOPER

CASM IT

:: SCREENSHOTS

N/a

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Perl

:: DOWNLOAD

AscatNGS

:: MORE INFORMATION

Citation

Raine KM, Van Loo P, Wedge DC, Jones D, Menzies A, Butler AP, Teague JW, Tarpey P, Nik-Zainal S, Campbell PJ.
ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data.
Curr Protoc Bioinformatics. 2016 Dec 8;56:15.9.1-15.9.17. doi: 10.1002/cpbi.17. PMID: 27930809; PMCID: PMC6097604.

IDEAFIX – Refinement of Variants in FFPE DNA Sequencing data

IDEAFIX

:: DESCRIPTION

IDEAFIX is a decision tree-based variant refinement tool that filters formaldehyde-induced cytosine deaminations from variant lists obtained from DNA sequencing data from FFPE specimens.

::DEVELOPER

Maitena Tellaetxe Abete

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • R

:: DOWNLOAD

IDEAFIX

:: MORE INFORMATION

Citation

Tellaetxe-Abete M, Calvo B, Lawrie C.
Ideafix: a decision tree-based method for the refinement of variants in FFPE DNA sequencing data.
NAR Genom Bioinform. 2021 Oct 27;3(4):lqab092. doi: 10.1093/nargab/lqab092. PMID: 34729472; PMCID: PMC8557387.

Sarek 2.7.1 – Detect Germline or Somatic Variants from Whole Genome or Targeted Sequencing

Sarek 2.7.1

:: DESCRIPTION

Sarek is a workflow designed to detect variants on whole genome or targeted sequencing data. Initially designed for Human, and Mouse, it can work on any species with a reference genome. Sarek can also handle tumour / normal pairs and could include additional relapses.

::DEVELOPER

the Science for Life Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Docker

:: DOWNLOAD

Sarek

:: MORE INFORMATION

Citation

Garcia M, Juhos S, Larsson M, Olason PI, Martin M, Eisfeldt J, DiLorenzo S, Sandgren J, Díaz De Ståhl T, Ewels P, Wirta V, Nistér M, Käller M, Nystedt B.
Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants.
F1000Res. 2020 Jan 29;9:63. doi: 10.12688/f1000research.16665.2. PMID: 32269765; PMCID: PMC7111497.

Calib v0.3.6 – Clustering UMI-barcoded Sequencing data

Calib v0.3.6

:: DESCRIPTION

Calib clusters barcode tagged paired-end reads based on their barcode and sequence similarity.

::DEVELOPER

Computational Methods for Paleogenomics and Comparative Genomics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • conda
  • Python

:: DOWNLOAD

Calib

:: MORE INFORMATION

Citation

Orabi B, Erhan E, McConeghy B, Volik SV, Le Bihan S, Bell R, Collins CC, Chauve C, Hach F.
Alignment-free clustering of UMI tagged DNA molecules.
Bioinformatics. 2019 Jun 1;35(11):1829-1836. doi: 10.1093/bioinformatics/bty888. PMID: 30351359.

DeepMP – Detect DNA modifications in Nanopore Sequencing data

DeepMP

:: DESCRIPTION

DeepMP is a convolutional neural network (CNN)-based model that takes information from Nanopore signals and basecalling errors to detect whether a read is methylated or not.

::DEVELOPER

DeepMP team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux
  • Python

:: DOWNLOAD

DeepMP

:: MORE INFORMATION

Citation:

Bonet J, Chen M, Dabad M, Heath S, Gonzalez-Perez A, Lopez-Bigas N, Lagergren J.
DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data.
Bioinformatics. 2021 Oct 28:btab745. doi: 10.1093/bioinformatics/btab745. Epub ahead of print. PMID: 34718417.

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